Clinical review: A review and analysis of heart rate variability and the diagnosis and prognosis of infection
Open accessAbstract
Bacterial infection leading to organ failure is the most common cause of death in critically ill patients. Early diagnosis and expeditious treatment is a cornerstone of therapy. Evaluating the systemic host response to infection as a complex system provides novel insights: however, bedside application with clinical value remains wanting. Providing an integrative measure of an altered host response, the patterns and character of heart rate fluctuations measured over intervals-in-time may be analysed with a panel of mathematical techniques that quantify overall fluctuation, spectral composition, scale-free variation, and degree of irregularity or complexity. Using these techniques, heart rate variability (HRV) has been documented to be both altered in the presence of systemic infection, and correlated with its severity. In this review and analysis, we evaluate the use of HRV monitoring to provide early diagnosis of infection, document the prognostic implications of altered HRV in infection, identify current limitations, highlight future research challenges, and propose improvement strategies. Given existing evidence and potential for further technological advances, we believe that longitudinal, individualized, and comprehensive HRV monitoring in critically ill patients at risk for or with existing infection offers a means to harness the clinical potential of this bedside application of complex systems science.
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The finding of association between reduced HRV and poor outcomes is consistent with the theory of 'critical slowing down'.
“This finding is consistent with the theory of “critical slowing down,” where decreasing variability in biological systems signals impending state transitions20.”
From Machine learning predicts sepsis deterioration trajectories. (2026) · cites this paper as [20]
The Prognostication section links reduced HRV measures with deterioration and mortality, and the Discussion links decreased variation with infection severity. But the paper does not identify this pattern as “critical slowing down” or say that decreasing variability signals impending state transitions. (LLM, conf=0.83)
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- Authors
- Ahmad, S., Tejuja, A., Newman, K. D., Zarychanski, R., & Seely, A. J.
- Affiliations
- Ottawa Hospital Research Institute (CA)
- CancerCare Manitoba (CA)
- University of Ottawa (CA)
- Corresponding author
- Seely, Andrew JE
- Venue
- Critical Care
- Published
- 2009
- Volume
- 13
- Issue
- 6
- Pages
- 232
- ISSN
- 1364-8535 (ISSN-L)
- PMC
- PMC2811891
- OpenAlex
- W2112011799
- Cited by
- 151
- References
- 68
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 7 · 2023: 6 · 2022: 12 · 2021: 17 · 2020: 17 · 2019: 11 · 2018: 7 · 2017: 9 · 2016: 11 · 2015: 9 · 2014: 8 · 2013: 11 · 2012: 7
- FWCI
- 0.85
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Critical Care (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Ottawa
- Ottawa Hospital Research Institute
- Canadian Institutes of Health Research
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- heart rate variability, bacterial infection, sepsis, early infection detection, prognosis, critically ill patients, complex systems science, spectral analysis of HRV, infection severity
- MeSH terms
- Bacterial Infections, Heart Rate, Humans, Prognosis, Resuscitation, Observer Variation, Critical Illness
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